Pan-cancer in silico analysis of somatic mutations in G-protein coupled receptors: The effect of evolutionary conservation and natural variance

Abstract

AbstractG protein-coupled receptors (GPCRs) form the most frequently exploited drug target family, moreover they are often found mutated in cancer. Here we used an aggregated dataset of mutations found in cancer patient samples derived from the Genomic Data Commons and compared it to the natural human variance as exemplified by data from the 1000 Genomes project. While the location of these mutations across the protein domains did not differ significantly in the two datasets, a mutation enrichment was observed in cancer patients among conserved residues in GPCRs such as the “DRY” motif. We subsequently created a ranking of high scoring GPCRs, using a multi-objective approach (Pareto Front Ranking). The validity of our approach was confirmed by re-discovery of established cancer targets such as the LPA and mGlu receptor families, and we identified novel GPCRs that had not been directly linked to cancer before such as the P2Y Receptor 10 (P2RY10). As a proof of concept, we projected the structurally investigated mutations in the crystal structure of the C-C Chemokine (CCR) 5 receptor, one of the high-ranking GPCRs previously linked to cancer. Several positions were pinpointed that relate to either structural integrity or endogenous and synthetic ligand binding, providing a rationale to their mechanism of influence in cancer. In conclusion, this study identifies a list of GPCRs that are prioritized for experimental follow up characterization to elucidate their role in cancer. The computational approach here described can be adapted to investigate the roles in cancer of any protein family.Author summaryDespite cancer being one of the most studied diseases due to its high mortality rate, one underexplored aspect is the association of certain protein families with tumor pathogenicity. We focused here on the G protein-coupled receptors family for three reasons. Firstly, it has been shown that this is the second most mutated class of proteins in cancer following kinases. Secondly, this family has been extensively studied resulting in a wide availability of experimental data for these proteins. Finally, more than 30 % of the drugs currently in the market target its members. For these receptors, we explored the mutational landscape across cancer patients compared to healthy individuals. Our findings show the existence of cancer-related alteration patterns that occur at conserved positions. Additionally, we computationally ranked these G protein-coupled receptors on their importance in the pathogenesis of cancer based on multiple objectives. The result is a list of recommendations on where to focus next. These results suggest that there is room for repurposing existing therapies for cancer treatment while also highlighting the risk of potential interactions between cancer treatments and common drugs. All in all, we present a window of opportunity for new targeting strategies in oncology for G protein-coupled receptors.